The potential impact of antiretroviral therapy of HIV-infected individuals and antiretroviral chemoprophylaxis of HIV susceptible individuals on the global spread of human immunodeficiency virus (HIV) is unknown and has not been adequately modeled. This proposal will investigate the effects of antiretroviral therapy and chemoprophylaxis on heterosexual spread of HIV using a new generation of mathematical and computational models that represent realistic biological and behavioral heterogeneities that underlie heterosexual spread of HIV. These innovative models: i) incorporate variation in plasma viremia, CD4 cell decline, HIV disease progression, infectiousness, risk behavior and response to antiretroviral therapy, both within and among individuals; ii) simulate different strategies of antiretroviral use; and iii) predict HIV epidemic outcomes at the population level. Our long-term goal is to use modeling and simulation to design public health interventions that will help control the global HIV epidemic. The central hypothesis is that targeting specific subpopulations of persons at highest risk for transmitting and acquiring HIV infection can maximize the impact of antiretrovirals on the HIV epidemic. The specific aims proposed are: 1) to develop and analyze a set of analogous yet increasingly accurate models of the heterosexual HIV epidemic in resource-limited settings, using three different modeling methods - differential equations, discrete event systems and exponential random graphs; 2) to identify which HIV-infected persons should receive antiretroviral therapy to maximize the effect of antiretroviral therapy on heterosexual transmission of HIV; and 3) to compare the effectiveness of antiretroviral therapy of infected individuals with antiretroviral chemoprophylaxis of HIV-susceptible persons. The proposed research is innovative in that we will use newly developed mathematical and computational models to simulate the effectiveness of different HIV prevention strategies in resource-limited settings. Our findings should help identify maximally effective antiretroviral strategies to curb the global spread of HIV.